{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入模块\n",
    "import pandas as pd\n",
    "import json\n",
    "from pyecharts.charts import Map\n",
    "from pyecharts import options as opts\n",
    "import random\n",
    "import datetime\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>豆瓣</th>\n",
       "      <th>rank</th>\n",
       "      <th>link</th>\n",
       "      <th>title</th>\n",
       "      <th>year</th>\n",
       "      <th>director</th>\n",
       "      <th>director_country</th>\n",
       "      <th>main_country_region_en</th>\n",
       "      <th>type</th>\n",
       "      <th>length</th>\n",
       "      <th>country_region</th>\n",
       "      <th>language</th>\n",
       "      <th>avg_rating</th>\n",
       "      <th>num_of_ratings</th>\n",
       "      <th>people_watched</th>\n",
       "      <th>people_wants_to_watch</th>\n",
       "      <th>num_comment</th>\n",
       "      <th>num_reviews</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>https://movie.douban.com/subject/1292052/</td>\n",
       "      <td>肖申克的救赎 The Shawshank Redemption</td>\n",
       "      <td>1994</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>法国</td>\n",
       "      <td>United States</td>\n",
       "      <td>犯罪剧情</td>\n",
       "      <td>142</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1326471</td>\n",
       "      <td>1684511</td>\n",
       "      <td>165409</td>\n",
       "      <td>262048</td>\n",
       "      <td>7472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>https://movie.douban.com/subject/1291546/</td>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>中国</td>\n",
       "      <td>China</td>\n",
       "      <td>剧情爱情同性</td>\n",
       "      <td>171</td>\n",
       "      <td>中国大陆 / 香港</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>9.6</td>\n",
       "      <td>979656</td>\n",
       "      <td>1354055</td>\n",
       "      <td>173918</td>\n",
       "      <td>212714</td>\n",
       "      <td>6198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>https://movie.douban.com/subject/1295644/</td>\n",
       "      <td>这个杀手不太冷 Léon</td>\n",
       "      <td>1994</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>法国</td>\n",
       "      <td>France</td>\n",
       "      <td>剧情动作犯罪</td>\n",
       "      <td>110分钟(剧场</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语 / 意大利语 / 法语</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1214394</td>\n",
       "      <td>1759981</td>\n",
       "      <td>150271</td>\n",
       "      <td>223117</td>\n",
       "      <td>4404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>https://movie.douban.com/subject/1292720/</td>\n",
       "      <td>阿甘正传 Forrest Gump</td>\n",
       "      <td>1994</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>剧情爱情</td>\n",
       "      <td>142</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1045020</td>\n",
       "      <td>1485661</td>\n",
       "      <td>132245</td>\n",
       "      <td>173452</td>\n",
       "      <td>3824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>https://movie.douban.com/subject/1292063/</td>\n",
       "      <td>美丽人生 La vita è bella</td>\n",
       "      <td>1997</td>\n",
       "      <td>罗伯托·贝尼尼</td>\n",
       "      <td>意大利</td>\n",
       "      <td>Italy</td>\n",
       "      <td>剧情喜剧爱情战争</td>\n",
       "      <td>116</td>\n",
       "      <td>意大利</td>\n",
       "      <td>意大利语 / 德语 / 英语</td>\n",
       "      <td>9.5</td>\n",
       "      <td>611313</td>\n",
       "      <td>776431</td>\n",
       "      <td>228473</td>\n",
       "      <td>128781</td>\n",
       "      <td>3028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>246</td>\n",
       "      <td>https://movie.douban.com/subject/1298653/</td>\n",
       "      <td>荒岛余生 Cast Away</td>\n",
       "      <td>2000</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>冒险剧情</td>\n",
       "      <td>143</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语 / 俄语</td>\n",
       "      <td>8.5</td>\n",
       "      <td>167150</td>\n",
       "      <td>248741</td>\n",
       "      <td>70889</td>\n",
       "      <td>25885</td>\n",
       "      <td>600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>247</td>\n",
       "      <td>https://movie.douban.com/subject/3592854/</td>\n",
       "      <td>疯狂的麦克斯4：狂暴之路 Mad Max: Fury Road</td>\n",
       "      <td>2015</td>\n",
       "      <td>乔治·米勒</td>\n",
       "      <td>澳大利亚</td>\n",
       "      <td>Iran</td>\n",
       "      <td>动作科幻冒险</td>\n",
       "      <td>120</td>\n",
       "      <td>澳大利亚 / 美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>8.6</td>\n",
       "      <td>257516</td>\n",
       "      <td>317328</td>\n",
       "      <td>54483</td>\n",
       "      <td>69446</td>\n",
       "      <td>514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>248</td>\n",
       "      <td>https://movie.douban.com/subject/1300741/</td>\n",
       "      <td>枪火 鎗火</td>\n",
       "      <td>1999</td>\n",
       "      <td>杜琪峰</td>\n",
       "      <td>中国</td>\n",
       "      <td>China</td>\n",
       "      <td>剧情动作犯罪</td>\n",
       "      <td>84分钟(香</td>\n",
       "      <td>香港</td>\n",
       "      <td>粤语</td>\n",
       "      <td>8.7</td>\n",
       "      <td>121544</td>\n",
       "      <td>158929</td>\n",
       "      <td>53724</td>\n",
       "      <td>22880</td>\n",
       "      <td>337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>249</td>\n",
       "      <td>https://movie.douban.com/subject/3217169/</td>\n",
       "      <td>勇士 Warrior</td>\n",
       "      <td>2011</td>\n",
       "      <td>加文·欧康诺</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>剧情家庭运动</td>\n",
       "      <td>140</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>8.9</td>\n",
       "      <td>101460</td>\n",
       "      <td>123540</td>\n",
       "      <td>66711</td>\n",
       "      <td>28326</td>\n",
       "      <td>580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>250</td>\n",
       "      <td>https://movie.douban.com/subject/1291936/</td>\n",
       "      <td>攻壳机动队 攻殻機動隊</td>\n",
       "      <td>1995</td>\n",
       "      <td>押井守</td>\n",
       "      <td>日本</td>\n",
       "      <td>Japan</td>\n",
       "      <td>动作科幻动画</td>\n",
       "      <td>83</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>8.9</td>\n",
       "      <td>74607</td>\n",
       "      <td>93323</td>\n",
       "      <td>57342</td>\n",
       "      <td>14575</td>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "豆瓣   rank                                       link  \\\n",
       "0       1  https://movie.douban.com/subject/1292052/   \n",
       "1       2  https://movie.douban.com/subject/1291546/   \n",
       "2       3  https://movie.douban.com/subject/1295644/   \n",
       "3       4  https://movie.douban.com/subject/1292720/   \n",
       "4       5  https://movie.douban.com/subject/1292063/   \n",
       "..    ...                                        ...   \n",
       "245   246  https://movie.douban.com/subject/1298653/   \n",
       "246   247  https://movie.douban.com/subject/3592854/   \n",
       "247   248  https://movie.douban.com/subject/1300741/   \n",
       "248   249  https://movie.douban.com/subject/3217169/   \n",
       "249   250  https://movie.douban.com/subject/1291936/   \n",
       "\n",
       "豆瓣                             title  year  director director_country  \\\n",
       "0    肖申克的救赎 The Shawshank Redemption  1994  弗兰克·德拉邦特               法国   \n",
       "1                               霸王别姬  1993       陈凯歌               中国   \n",
       "2                       这个杀手不太冷 Léon  1994     吕克·贝松               法国   \n",
       "3                  阿甘正传 Forrest Gump  1994  罗伯特·泽米吉斯               美国   \n",
       "4               美丽人生 La vita è bella  1997   罗伯托·贝尼尼              意大利   \n",
       "..                               ...   ...       ...              ...   \n",
       "245                   荒岛余生 Cast Away  2000  罗伯特·泽米吉斯               美国   \n",
       "246  疯狂的麦克斯4：狂暴之路 Mad Max: Fury Road  2015     乔治·米勒             澳大利亚   \n",
       "247                            枪火 鎗火  1999       杜琪峰               中国   \n",
       "248                       勇士 Warrior  2011    加文·欧康诺               美国   \n",
       "249                      攻壳机动队 攻殻機動隊  1995       押井守               日本   \n",
       "\n",
       "豆瓣  main_country_region_en      type    length country_region        language  \\\n",
       "0            United States      犯罪剧情       142             美国              英语   \n",
       "1                    China    剧情爱情同性       171      中国大陆 / 香港           汉语普通话   \n",
       "2                   France    剧情动作犯罪  110分钟(剧场             法国  英语 / 意大利语 / 法语   \n",
       "3            United States      剧情爱情       142             美国              英语   \n",
       "4                    Italy  剧情喜剧爱情战争       116            意大利  意大利语 / 德语 / 英语   \n",
       "..                     ...       ...       ...            ...             ...   \n",
       "245          United States      冒险剧情       143             美国         英语 / 俄语   \n",
       "246                   Iran    动作科幻冒险       120      澳大利亚 / 美国              英语   \n",
       "247                  China    剧情动作犯罪    84分钟(香             香港              粤语   \n",
       "248          United States    剧情家庭运动       140             美国              英语   \n",
       "249                  Japan    动作科幻动画        83             日本              日语   \n",
       "\n",
       "豆瓣   avg_rating  num_of_ratings  people_watched  people_wants_to_watch  \\\n",
       "0           9.6         1326471         1684511                 165409   \n",
       "1           9.6          979656         1354055                 173918   \n",
       "2           9.4         1214394         1759981                 150271   \n",
       "3           9.4         1045020         1485661                 132245   \n",
       "4           9.5          611313          776431                 228473   \n",
       "..          ...             ...             ...                    ...   \n",
       "245         8.5          167150          248741                  70889   \n",
       "246         8.6          257516          317328                  54483   \n",
       "247         8.7          121544          158929                  53724   \n",
       "248         8.9          101460          123540                  66711   \n",
       "249         8.9           74607           93323                  57342   \n",
       "\n",
       "豆瓣   num_comment  num_reviews  \n",
       "0         262048         7472  \n",
       "1         212714         6198  \n",
       "2         223117         4404  \n",
       "3         173452         3824  \n",
       "4         128781         3028  \n",
       "..           ...          ...  \n",
       "245        25885          600  \n",
       "246        69446          514  \n",
       "247        22880          337  \n",
       "248        28326          580  \n",
       "249        14575          220  \n",
       "\n",
       "[250 rows x 17 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 简化栏位变数名称\n",
    "# 打开文档\n",
    "df = pd.read_csv (\"douban_250_1.csv\", encoding = \"utf-8\")\n",
    "douban = df.copy() \n",
    "douban.columns.name = \"豆瓣\"\n",
    "douban"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>director</th>\n",
       "      <th>avg_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>宫崎骏</td>\n",
       "      <td>62.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>62.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>史蒂文·斯皮尔伯格</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>王家卫</td>\n",
       "      <td>43.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>李安</td>\n",
       "      <td>35.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>宁浩</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>克里斯托弗·史密斯</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>邓肯·琼斯</td>\n",
       "      <td>8.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>汤姆·霍珀</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>普特鹏·普罗萨卡·那·萨克那卡林</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             director  avg_rating\n",
       "0                 宫崎骏        62.7\n",
       "1            克里斯托弗·诺兰        62.6\n",
       "2           史蒂文·斯皮尔伯格        53.0\n",
       "3                 王家卫        43.3\n",
       "4                  李安        35.7\n",
       "..                ...         ...\n",
       "170                宁浩         8.4\n",
       "171         克里斯托弗·史密斯         8.4\n",
       "172             邓肯·琼斯         8.4\n",
       "173             汤姆·霍珀         8.3\n",
       "174  普特鹏·普罗萨卡·那·萨克那卡林         8.3\n",
       "\n",
       "[175 rows x 2 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 数据重塑：国内影响力大的导演\n",
    "# 参数axis只有两个值，分别是0和1，而df中只有两个index分别是表最左一列的时间和表最上一行\n",
    "# ascending=False代表降序，ascending=True代表升序\n",
    "# sort_values 按照by后面的数值排序\n",
    "douban_daoyan = douban.groupby([\"director\"]).agg({\"avg_rating\":\"sum\"})\\\n",
    "                 .sort_values(by=\"avg_rating\", ascending=False).reset_index()\n",
    "douban_daoyan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "k=zip(list(douban_daoyan.director),list(douban_daoyan.avg_rating))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['宫崎骏',\n",
       " '克里斯托弗·诺兰',\n",
       " '史蒂文·斯皮尔伯格',\n",
       " '王家卫',\n",
       " '李安',\n",
       " '大卫·芬奇',\n",
       " '朱塞佩·托纳多雷',\n",
       " '彼得·杰克逊',\n",
       " '弗朗西斯·福特·科波拉',\n",
       " '刘镇伟',\n",
       " '姜文',\n",
       " '詹姆斯·卡梅隆',\n",
       " '是枝裕和',\n",
       " '理查德·林克莱特',\n",
       " '彼特·道格特',\n",
       " '昆汀·塔伦蒂诺',\n",
       " '理查德·柯蒂斯',\n",
       " '吴宇森',\n",
       " '查理·卓别林',\n",
       " '弗兰克·德拉邦特',\n",
       " '彼得·威尔',\n",
       " '赛尔乔·莱昂内',\n",
       " '吕克·贝松',\n",
       " '森淳一',\n",
       " '罗伯特·泽米吉斯',\n",
       " '黑泽明',\n",
       " '李·昂克里奇',\n",
       " '杨德昌',\n",
       " '今敏',\n",
       " '中岛哲也',\n",
       " '蒂姆·波顿',\n",
       " '梅尔·吉布森',\n",
       " '罗伯·莱纳',\n",
       " '莉莉·沃卓斯基',\n",
       " '爱德华·兹威克',\n",
       " '保罗·格林格拉斯',\n",
       " '雷德利·斯科特',\n",
       " '安德鲁·尼科尔',\n",
       " '达伦·阿伦诺夫斯基',\n",
       " '斯坦利·库布里克',\n",
       " '丹尼·博伊尔',\n",
       " '新海诚',\n",
       " '比利·怀德',\n",
       " '陈凯歌',\n",
       " '罗伯托·贝尼尼',\n",
       " '西德尼·吕美特',\n",
       " '万籁鸣',\n",
       " '克里斯托夫·巴拉蒂',\n",
       " '黄东赫',\n",
       " '路易·西霍尤斯',\n",
       " '安德鲁·斯坦顿',\n",
       " '拉斯·霍尔斯道姆',\n",
       " '杨宇硕',\n",
       " '奥利维埃·纳卡什',\n",
       " '拉吉库马尔·希拉尼',\n",
       " '马基德·马基迪',\n",
       " '李濬益',\n",
       " '张艺谋',\n",
       " '拜伦·霍华德',\n",
       " '维克多·弗莱明',\n",
       " '小津安二郎',\n",
       " '米洛斯·福尔曼',\n",
       " '托马斯·温特伯格',\n",
       " '阿兰·葛斯彭纳',\n",
       " '盖·里奇',\n",
       " '贝纳尔多·贝托鲁奇',\n",
       " '刘伟强',\n",
       " '神山征二郎',\n",
       " '罗曼·波兰斯基',\n",
       " '王树忱',\n",
       " '弗洛里安·亨克尔·冯·多纳斯马尔克',\n",
       " '罗伯特·怀斯',\n",
       " '克林特·伊斯特伍德',\n",
       " '斯坦利·多南',\n",
       " '秋昌旼',\n",
       " '马克·赫尔曼',\n",
       " '马丁·布莱斯特',\n",
       " '雅克·贝汉',\n",
       " '加布里埃莱·穆奇诺',\n",
       " '威廉·惠勒',\n",
       " '涅提·蒂瓦里',\n",
       " '阿米尔·汗',\n",
       " '卡迪亚·兰德',\n",
       " '亚当·艾略特',\n",
       " '杰茜·尼尔森',\n",
       " '加文·欧康诺',\n",
       " '阿尔弗雷德·希区柯克',\n",
       " '押井守',\n",
       " '特瑞·乔治',\n",
       " '岩井俊二',\n",
       " '罗杰·阿勒斯',\n",
       " '严定宪',\n",
       " '朗·霍华德',\n",
       " '克里斯·哥伦布',\n",
       " '热拉尔·乌里',\n",
       " '卢卡·瓜达尼诺',\n",
       " '茂文·勒鲁瓦',\n",
       " '詹姆斯·麦克特格',\n",
       " '达米安·斯兹弗隆',\n",
       " '近藤喜文',\n",
       " '陈可辛',\n",
       " '韦斯·安德森',\n",
       " '藤森雅也',\n",
       " 'M·奈特·沙马兰',\n",
       " '泷田洋二郎',\n",
       " '北野武',\n",
       " '格斯·范·桑特',\n",
       " '托尼·凯耶',\n",
       " '乔纳森·戴米',\n",
       " '汉内斯·赫尔姆',\n",
       " '李焕庆',\n",
       " '大森贵弘',\n",
       " '伦尼·阿伯拉罕森',\n",
       " '汤姆·麦卡锡',\n",
       " '姜炯哲',\n",
       " '让-马克·瓦雷',\n",
       " '让-皮埃尔·热内',\n",
       " '巴瑞·莱文森',\n",
       " '迪恩·德布洛斯',\n",
       " '詹姆斯·曼高德',\n",
       " '忻钰坤',\n",
       " '郭柯',\n",
       " '阿斯哈·法哈蒂',\n",
       " '金秉祐',\n",
       " '奥里奥尔·保罗',\n",
       " '奉俊昊',\n",
       " '陆川',\n",
       " '大卫·叶茨',\n",
       " '埃里克·布雷斯',\n",
       " '马丁·斯科塞斯',\n",
       " '马丁·麦克唐纳',\n",
       " '高畑勋',\n",
       " '戈尔·维宾斯基',\n",
       " '温子仁',\n",
       " '程小东',\n",
       " '丹尼斯·甘塞尔',\n",
       " '柯克·德·米科',\n",
       " '米林宏昌',\n",
       " '杜琪峰',\n",
       " '瑞奇·摩尔',\n",
       " '罗启锐',\n",
       " '周星驰',\n",
       " '迈克尔·贝',\n",
       " '迈克尔·柯蒂兹',\n",
       " '达米恩·查泽雷',\n",
       " '布莱恩·辛格',\n",
       " '肯尼思·洛纳根',\n",
       " '保罗·哈吉斯',\n",
       " '乔治·米勒',\n",
       " '细田守',\n",
       " '莫滕·泰杜姆',\n",
       " '西恩·潘',\n",
       " '唐·霍尔',\n",
       " '皮埃尔·柯芬',\n",
       " '保罗·格诺维塞',\n",
       " '卡比尔·汗',\n",
       " '卡洛斯·沙尔丹哈',\n",
       " '乔·赖特',\n",
       " '史蒂芬·戴德利',\n",
       " '理查德·沙因克曼',\n",
       " '詹姆斯·沃德·布柯特',\n",
       " '约翰·卡尼',\n",
       " '李惠民',\n",
       " '萨姆·门德斯',\n",
       " '道格·里曼',\n",
       " '安东尼·明格拉',\n",
       " '尼克·卡萨维茨',\n",
       " '李力持',\n",
       " '徐克',\n",
       " '汤姆·提克威',\n",
       " '宁浩',\n",
       " '克里斯托弗·史密斯',\n",
       " '邓肯·琼斯',\n",
       " '汤姆·霍珀',\n",
       " '普特鹏·普罗萨卡·那·萨克那卡林']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(douban_daoyan.director)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['62.7',\n",
       " '62.6',\n",
       " '53.0',\n",
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       " '27.2',\n",
       " '27.1',\n",
       " '27.1',\n",
       " '26.8',\n",
       " '26.7',\n",
       " '26.6',\n",
       " '26.6',\n",
       " '26.4',\n",
       " '26.2',\n",
       " '25.9',\n",
       " '25.8',\n",
       " '25.7',\n",
       " '18.5',\n",
       " '18.3',\n",
       " '18.2',\n",
       " '18.2',\n",
       " '18.1',\n",
       " '17.9',\n",
       " '17.9',\n",
       " '17.9',\n",
       " '17.8',\n",
       " '17.8',\n",
       " '17.8',\n",
       " '17.6',\n",
       " '17.5',\n",
       " '17.5',\n",
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       " '16.7',\n",
       " '9.6',\n",
       " '9.6',\n",
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       " '9.4',\n",
       " '9.3',\n",
       " '9.3',\n",
       " '9.3',\n",
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       " '9.3',\n",
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       " '9.2',\n",
       " '9.2',\n",
       " '9.2',\n",
       " '9.2',\n",
       " '9.2',\n",
       " '9.2',\n",
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       " '9.1',\n",
       " '9.1',\n",
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       " '9.0',\n",
       " '9.0',\n",
       " '9.0',\n",
       " '9.0',\n",
       " '9.0',\n",
       " '9.0',\n",
       " '9.0',\n",
       " '9.0',\n",
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       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.9',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.8',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.7',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.6',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.5',\n",
       " '8.4',\n",
       " '8.4',\n",
       " '8.4',\n",
       " '8.4',\n",
       " '8.3',\n",
       " '8.3']"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = list(douban_daoyan.avg_rating)\n",
    "k = ['{:.1f}'.format(i) for i in b]\n",
    "k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "                    \"name\": \"\\u9ed1\\u6cfd\\u660e\",\n",
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       "                {\n",
       "                    \"name\": \"\\u674e\\u00b7\\u6602\\u514b\\u91cc\\u5947\",\n",
       "                    \"value\": \"17.8\"\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                    \"value\": \"17.6\"\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u7231\\u5fb7\\u534e\\u00b7\\u5179\\u5a01\\u514b\",\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                {\n",
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       "                \"\\u5e03\\u83b1\\u6069\\u00b7\\u8f9b\\u683c\",\n",
       "                \"\\u80af\\u5c3c\\u601d\\u00b7\\u6d1b\\u7eb3\\u6839\",\n",
       "                \"\\u4fdd\\u7f57\\u00b7\\u54c8\\u5409\\u65af\",\n",
       "                \"\\u4e54\\u6cbb\\u00b7\\u7c73\\u52d2\",\n",
       "                \"\\u7ec6\\u7530\\u5b88\",\n",
       "                \"\\u83ab\\u6ed5\\u00b7\\u6cf0\\u675c\\u59c6\",\n",
       "                \"\\u897f\\u6069\\u00b7\\u6f58\",\n",
       "                \"\\u5510\\u00b7\\u970d\\u5c14\",\n",
       "                \"\\u76ae\\u57c3\\u5c14\\u00b7\\u67ef\\u82ac\",\n",
       "                \"\\u4fdd\\u7f57\\u00b7\\u683c\\u8bfa\\u7ef4\\u585e\",\n",
       "                \"\\u5361\\u6bd4\\u5c14\\u00b7\\u6c57\",\n",
       "                \"\\u5361\\u6d1b\\u65af\\u00b7\\u6c99\\u5c14\\u4e39\\u54c8\",\n",
       "                \"\\u4e54\\u00b7\\u8d56\\u7279\",\n",
       "                \"\\u53f2\\u8482\\u82ac\\u00b7\\u6234\\u5fb7\\u5229\",\n",
       "                \"\\u7406\\u67e5\\u5fb7\\u00b7\\u6c99\\u56e0\\u514b\\u66fc\",\n",
       "                \"\\u8a79\\u59c6\\u65af\\u00b7\\u6c83\\u5fb7\\u00b7\\u5e03\\u67ef\\u7279\",\n",
       "                \"\\u7ea6\\u7ff0\\u00b7\\u5361\\u5c3c\",\n",
       "                \"\\u674e\\u60e0\\u6c11\",\n",
       "                \"\\u8428\\u59c6\\u00b7\\u95e8\\u5fb7\\u65af\",\n",
       "                \"\\u9053\\u683c\\u00b7\\u91cc\\u66fc\",\n",
       "                \"\\u5b89\\u4e1c\\u5c3c\\u00b7\\u660e\\u683c\\u62c9\",\n",
       "                \"\\u5c3c\\u514b\\u00b7\\u5361\\u8428\\u7ef4\\u8328\",\n",
       "                \"\\u674e\\u529b\\u6301\",\n",
       "                \"\\u5f90\\u514b\",\n",
       "                \"\\u6c64\\u59c6\\u00b7\\u63d0\\u514b\\u5a01\",\n",
       "                \"\\u5b81\\u6d69\",\n",
       "                \"\\u514b\\u91cc\\u65af\\u6258\\u5f17\\u00b7\\u53f2\\u5bc6\\u65af\",\n",
       "                \"\\u9093\\u80af\\u00b7\\u743c\\u65af\",\n",
       "                \"\\u6c64\\u59c6\\u00b7\\u970d\\u73c0\",\n",
       "                \"\\u666e\\u7279\\u9e4f\\u00b7\\u666e\\u7f57\\u8428\\u5361\\u00b7\\u90a3\\u00b7\\u8428\\u514b\\u90a3\\u5361\\u6797\"\n",
       "            ],\n",
       "            \"selected\": {},\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_417b725608a24398a2e98b92f37f6717.setOption(option_417b725608a24398a2e98b92f37f6717);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x259c43b59c8>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import Pie\n",
    "from pyecharts.faker import Faker\n",
    "\n",
    "\n",
    "v = list(douban_daoyan.director)\n",
    "b = list(douban_daoyan.avg_rating)\n",
    "k = ['{:.1f}'.format(i) for i in b]\n",
    "\n",
    "c = (\n",
    "    Pie(\n",
    "            ## 初始化配置项\n",
    "        init_opts=opts.InitOpts(\n",
    "            #设置动画\n",
    "            animation_opts=opts.AnimationOpts(animation_delay=1000, animation_easing=\"elasticOut\"),\n",
    "            #设置宽度、高度\n",
    "            width='900px',\n",
    "            height='1150px', \n",
    "        )\n",
    "    )\n",
    "    .add(\n",
    "        \"豆瓣最具影响力导演\",\n",
    "        [list(z) for z in zip(v, k)],\n",
    "        radius=[\"30%\", \"75%\"],\n",
    "        center=[\"50%\", \"75%\"],\n",
    "        rosetype=\"radius\",\n",
    "        label_opts=opts.LabelOpts(is_show=False),\n",
    "    )\n",
    "\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"\"))\n",
    ")\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\17719\\\\Downloads\\\\pandas\\\\20春_pandas_week11\\\\meiguitu.html'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 取前43名导演进行排序\n",
    "c = (\n",
    "    Pie(\n",
    "            ## 初始化配置项\n",
    "        init_opts=opts.InitOpts(\n",
    "            #设置动画\n",
    "            animation_opts=opts.AnimationOpts(animation_delay=1000, animation_easing=\"elasticOut\"),\n",
    "            #设置宽度、高度\n",
    "            width='900px',\n",
    "            height='500px', \n",
    "        )\n",
    "    )\n",
    "    .add(\n",
    "        \"豆瓣最具影响力前43名导演\",\n",
    "        [list(z) for z in zip(v[:42], k[:42])],\n",
    "        radius=[\"30%\", \"75%\"],\n",
    "        center=[\"50%\", \"65%\"],\n",
    "        rosetype=\"radius\",\n",
    "        label_opts=opts.LabelOpts(is_show=False),\n",
    "    )\n",
    "\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"\"))\n",
    ")\n",
    "c.render(\"meiguitu.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>director_country</th>\n",
       "      <th>director</th>\n",
       "      <th>title</th>\n",
       "      <th>评分</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>韩国</td>\n",
       "      <td>黄东赫</td>\n",
       "      <td>熔炉 도가니</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>韩国</td>\n",
       "      <td>奉俊昊</td>\n",
       "      <td>杀人回忆 살인의 추억</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>韩国</td>\n",
       "      <td>金秉祐</td>\n",
       "      <td>恐怖直播 더 테러 라이브</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>韩国</td>\n",
       "      <td>秋昌旼</td>\n",
       "      <td>我爱你 그대를 사랑합니다</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>韩国</td>\n",
       "      <td>杨宇硕</td>\n",
       "      <td>辩护人 변호인</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>中国</td>\n",
       "      <td>杨德昌</td>\n",
       "      <td>牯岭街少年杀人事件 牯嶺街少年殺人事件</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>中国</td>\n",
       "      <td>杨德昌</td>\n",
       "      <td>一一</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>中国</td>\n",
       "      <td>杜琪峰</td>\n",
       "      <td>枪火 鎗火</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>中国</td>\n",
       "      <td>李惠民</td>\n",
       "      <td>新龙门客栈 新龍門客棧</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>中国</td>\n",
       "      <td>万籁鸣</td>\n",
       "      <td>大闹天宫</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    director_country director                title   评分\n",
       "0                 韩国      黄东赫               熔炉 도가니  9.3\n",
       "1                 韩国      奉俊昊          杀人回忆 살인의 추억  8.7\n",
       "2                 韩国      金秉祐        恐怖直播 더 테러 라이브  8.7\n",
       "3                 韩国      秋昌旼        我爱你 그대를 사랑합니다  9.0\n",
       "4                 韩国      杨宇硕              辩护人 변호인  9.2\n",
       "..               ...      ...                  ...  ...\n",
       "245               中国      杨德昌  牯岭街少年杀人事件 牯嶺街少年殺人事件  8.8\n",
       "246               中国      杨德昌                   一一  9.0\n",
       "247               中国      杜琪峰                枪火 鎗火  8.7\n",
       "248               中国      李惠民          新龙门客栈 新龍門客棧  8.5\n",
       "249               中国      万籁鸣                 大闹天宫  9.3\n",
       "\n",
       "[250 rows x 4 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "douban_daoyanguoji = douban.groupby(by = [\"director_country\",\"director\",\"title\"]).agg({\"avg_rating\":\"sum\"}) \\\n",
    "                 .rename(columns = {\"avg_rating\":\"评分\"})\\\n",
    "                 .sort_values(by=\"director_country\", ascending=False).reset_index()\n",
    "\n",
    "douban_daoyanguoji"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['韩国', '阿根廷', '西班牙', '英格兰', '英国', '美国', '瑞士', '瑞典', '爱尔兰', '澳大利亚', '泰国', '法国', '日本', '新西兰', '捷克', '挪威', '意大利', '德国', '巴西', '印度', '匈牙利', '加拿大', '伊朗', '丹麦', '中国']\n"
     ]
    }
   ],
   "source": [
    "x=list(douban_daoyanguoji.director_country)\n",
    "s = []                          #创建一个新列表\n",
    "for i in x:                    #循环list里的每一个元素\n",
    "     if  i  not in s:            #判断元素是否存在新列表中，不存在则添加，存在则跳过，以此去重\n",
    "         s.append(i)\n",
    "        \n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[8,\n",
       " 1,\n",
       " 1,\n",
       " 1,\n",
       " 30,\n",
       " 80,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 1,\n",
       " 11,\n",
       " 32,\n",
       " 5,\n",
       " 1,\n",
       " 1,\n",
       " 10,\n",
       " 3,\n",
       " 2,\n",
       " 4,\n",
       " 1,\n",
       " 6,\n",
       " 2,\n",
       " 1,\n",
       " 38]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def countX(x, cc):\n",
    "    count = 0\n",
    "    for ele in x:\n",
    "        if (ele == cc):\n",
    "            count = count + 1\n",
    "    return count\n",
    "a = []\n",
    "for b in s:\n",
    "    a.append((countX(x,b)))\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'韩国': 8,\n",
       " '阿根廷': 1,\n",
       " '西班牙': 1,\n",
       " '英格兰': 1,\n",
       " '英国': 30,\n",
       " '美国': 80,\n",
       " '瑞士': 1,\n",
       " '瑞典': 2,\n",
       " '爱尔兰': 2,\n",
       " '澳大利亚': 6,\n",
       " '泰国': 1,\n",
       " '法国': 11,\n",
       " '日本': 32,\n",
       " '新西兰': 5,\n",
       " '捷克': 1,\n",
       " '挪威': 1,\n",
       " '意大利': 10,\n",
       " '德国': 3,\n",
       " '巴西': 2,\n",
       " '印度': 4,\n",
       " '匈牙利': 1,\n",
       " '加拿大': 6,\n",
       " '伊朗': 2,\n",
       " '丹麦': 1,\n",
       " '中国': 38}"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e = dict(zip(s,a))\n",
    "e"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>director</th>\n",
       "      <th>title</th>\n",
       "      <th>director_country</th>\n",
       "      <th>main_country_region_en</th>\n",
       "      <th>avg_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1931</td>\n",
       "      <td>查理·卓别林</td>\n",
       "      <td>城市之光 City Lights</td>\n",
       "      <td>英国</td>\n",
       "      <td>United States</td>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1936</td>\n",
       "      <td>查理·卓别林</td>\n",
       "      <td>摩登时代 Modern Times</td>\n",
       "      <td>英国</td>\n",
       "      <td>United States</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1939</td>\n",
       "      <td>维克多·弗莱明</td>\n",
       "      <td>乱世佳人 Gone with the Wind</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>9.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1940</td>\n",
       "      <td>茂文·勒鲁瓦</td>\n",
       "      <td>魂断蓝桥 Waterloo Bridge</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1942</td>\n",
       "      <td>迈克尔·柯蒂兹</td>\n",
       "      <td>卡萨布兰卡 Casablanca</td>\n",
       "      <td>匈牙利</td>\n",
       "      <td>United States</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>2016</td>\n",
       "      <td>涅提·蒂瓦里</td>\n",
       "      <td>摔跤吧！爸爸 Dangal</td>\n",
       "      <td>印度</td>\n",
       "      <td>India</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>2016</td>\n",
       "      <td>肯尼思·洛纳根</td>\n",
       "      <td>海边的曼彻斯特 Manchester by the Sea</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>2017</td>\n",
       "      <td>李·昂克里奇</td>\n",
       "      <td>寻梦环游记 Coco</td>\n",
       "      <td>美国</td>\n",
       "      <td>United States</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>2017</td>\n",
       "      <td>卢卡·瓜达尼诺</td>\n",
       "      <td>请以你的名字呼唤我 Call Me by Your Name</td>\n",
       "      <td>意大利</td>\n",
       "      <td>Italy</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>2017</td>\n",
       "      <td>马丁·麦克唐纳</td>\n",
       "      <td>三块广告牌 Three Billboards Outside Ebbing, Missouri</td>\n",
       "      <td>英国</td>\n",
       "      <td>United States</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>250 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     year director                                            title  \\\n",
       "0    1931   查理·卓别林                                 城市之光 City Lights   \n",
       "1    1936   查理·卓别林                                摩登时代 Modern Times   \n",
       "2    1939  维克多·弗莱明                          乱世佳人 Gone with the Wind   \n",
       "3    1940   茂文·勒鲁瓦                             魂断蓝桥 Waterloo Bridge   \n",
       "4    1942  迈克尔·柯蒂兹                                 卡萨布兰卡 Casablanca   \n",
       "..    ...      ...                                              ...   \n",
       "245  2016   涅提·蒂瓦里                                    摔跤吧！爸爸 Dangal   \n",
       "246  2016  肯尼思·洛纳根                    海边的曼彻斯特 Manchester by the Sea   \n",
       "247  2017   李·昂克里奇                                       寻梦环游记 Coco   \n",
       "248  2017  卢卡·瓜达尼诺                   请以你的名字呼唤我 Call Me by Your Name   \n",
       "249  2017  马丁·麦克唐纳  三块广告牌 Three Billboards Outside Ebbing, Missouri   \n",
       "\n",
       "    director_country main_country_region_en  avg_rating  \n",
       "0                 英国          United States         9.3  \n",
       "1                 英国          United States         9.2  \n",
       "2                 美国          United States         9.2  \n",
       "3                 美国          United States         8.8  \n",
       "4                匈牙利          United States         8.6  \n",
       "..               ...                    ...         ...  \n",
       "245               印度                  India         9.0  \n",
       "246               美国          United States         8.6  \n",
       "247               美国          United States         9.0  \n",
       "248              意大利                  Italy         8.8  \n",
       "249               英国          United States         8.7  \n",
       "\n",
       "[250 rows x 6 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "douban_电影产出 = douban.groupby(by = [\"year\",\"director\",\"title\",\"director_country\",\"main_country_region_en\"]).agg({\"avg_rating\":\"sum\"}) \\\n",
    "                 .sort_values(by=\"year\", ascending=True).reset_index()\n",
    "\n",
    "douban_电影产出"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['United States', 'Japan', 'China', 'France', 'Italy', 'United Kingdom', 'Germany', 'Iran', 'New Zealand', 'Brazil', 'Korea', 'India', 'Australia', 'Thailand', 'Denmark', 'Argentina', 'Sweden', 'Ireland', 'Spain']\n"
     ]
    }
   ],
   "source": [
    "xx=list(douban_电影产出.main_country_region_en)\n",
    "ss = []                          #创建一个新列表\n",
    "for i in xx:                    #循环list里的每一个元素\n",
    "     if  i  not in ss:            #判断元素是否存在新列表中，不存在则添加，存在则跳过，以此去重\n",
    "         ss.append(i)\n",
    "        \n",
    "print(ss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    });\n",
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       "\n",
       "        <div id=\"a12a22d19fb740629ce3295d2206a635\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
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       "                    document.getElementById('a12a22d19fb740629ce3295d2206a635'), 'white', {renderer: 'canvas'});\n",
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       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
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       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"wordCloud\",\n",
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       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(11,9,51)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5df4\\u897f\",\n",
       "                    \"value\": 2,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(51,48,7)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5370\\u5ea6\",\n",
       "                    \"value\": 4,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(69,102,129)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5308\\u7259\\u5229\",\n",
       "                    \"value\": 1,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(155,50,93)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u52a0\\u62ff\\u5927\",\n",
       "                    \"value\": 6,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(82,103,151)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4f0a\\u6717\",\n",
       "                    \"value\": 2,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(109,88,157)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e39\\u9ea6\",\n",
       "                    \"value\": 1,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(122,132,94)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e2d\\u56fd\",\n",
       "                    \"value\": 38,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(72,105,88)\"\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            ],\n",
       "            \"drawOutOfBound\": false,\n",
       "            \"textStyle\": {\n",
       "                \"emphasis\": {}\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [],\n",
       "            \"selected\": {},\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u7535\\u5f71\\u4ea7\\u5730\\u70ed\\u70b9\\u5206\\u6790\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_a12a22d19fb740629ce3295d2206a635.setOption(option_a12a22d19fb740629ce3295d2206a635);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x259c4372a88>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import WordCloud\n",
    "from pyecharts.globals import SymbolType\n",
    "\n",
    "\n",
    "words = [list(z) for z in zip(list(s), list(a))]\n",
    "c = (\n",
    "    WordCloud()\n",
    "    .add(\"\", words, word_size_range=[30, 100], shape=SymbolType.DIAMOND)\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"电影产地热点分析\"))\n",
    ")\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "def countX(xx, ccc):\n",
    "    count = 0\n",
    "    for ele in xx:\n",
    "        if (ele == ccc):\n",
    "            count = count + 1\n",
    "    return count\n",
    "aa = []\n",
    "for b in ss:\n",
    "    aa.append((countX(xx,b)))\n",
    "aa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['韩国',\n",
       " '阿根廷',\n",
       " '西班牙',\n",
       " '英格兰',\n",
       " '英国',\n",
       " '美国',\n",
       " '瑞士',\n",
       " '瑞典',\n",
       " '爱尔兰',\n",
       " '澳大利亚',\n",
       " '泰国',\n",
       " '法国',\n",
       " '日本',\n",
       " '新西兰',\n",
       " '捷克',\n",
       " '挪威',\n",
       " '意大利',\n",
       " '德国',\n",
       " '巴西',\n",
       " '印度',\n",
       " '匈牙利',\n",
       " '加拿大',\n",
       " '伊朗',\n",
       " '丹麦',\n",
       " '中国']"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\17719\\\\Downloads\\\\pandas\\\\20春_pandas_week11\\\\dianyingchandiditu.html'"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import Map\n",
    "\n",
    "c = (\n",
    "    Map()\n",
    "    .add(\"商家A\", [list(z) for z in zip(ss, a)], \"world\")\n",
    "    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))\n",
    "    .set_global_opts(\n",
    "        title_opts=opts.TitleOpts(title=\"Map-世界电影产地地图\"),\n",
    "        visualmap_opts=opts.VisualMapOpts(max_=8),\n",
    "    )\n",
    ")\n",
    "c.render(\"dianyingchandiditu.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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